# Terrorism detection using Logistic Regression Algorithm in Python

So, here we’ll be looking at a Python implementation of the logistic regression algorithm. We will be using the dataset available below to implement our algorithm. The dataset consists of details of employees in a company. It contains the employee id, gender salary, and the purchase.

Dataset:-User_Data.csv

We make a logistic regression model that will predict whether the employee will buy the product or not.

Importing the libraries:

```import pandas as pnd
import numpy as nmp
import matplotlib.pyplot as pt
```

```dataset = pnd.read_csv('...\\User_Data.csv')
```

Now we need to find a relation between age and salary to predict whether the employee will purchase the product or not.

```x = dataset.iloc[:, [2, 3]].values
y = dataset.iloc[:, 4].values
```

Now we need to split the dataset. For training the model, 75% of data is used and for testing the model, 25% of the data is used.

```from sklearn.cross_validation import train_test_split
xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size = 0.25, random_state = 0)
```

Now we will perform the feature scaling operation between the age and salary so that the salary doesn’t dominate the age when it finds the nearest neighbor.

```from sklearn.preprocessing import StandardScaler
sc_x = StandardScaler()
xtrain = sc_x.fit_transform(xtrain)
xtest = sc_x.transform(xtest)
print (xtrain[0:10, :])
```

At last, we train our logistic regression model.

```from sklearn.linear_model import LogisticRegression
classifier = LogisticRegression(random_state = 0)
classifier.fit(xtrain, ytrain)
```

For the prediction,

```y_pred = classifier.predict(xtest)
```

Testing the performance,

```from sklearn.metrics import confusion_matrix
cm = confusion_matrix(ytest, y_pred)
print ("Confusion Matrix Output: \n", cm)
```

Output:

```Confusion Matrix :
[[65  3]
[ 8 24]]

TP+TN=65+24
FP+FN=8+3```

Finally the accuracy

```from sklearn.metrics import accuracy_score
print ("Accuracy : ", accuracy_score(ytest, y_pred))
```

Output:

```Accuracy :  0.89

```

By this method, we can easily implement the logistic regression algorithm. Implement this algorithm on the Global Terrorism Database(GTD) for the required result. I hope you have clearly understood the concept. For any clarifications or suggestions comment down below.